Background The facial expression of medical staff has been known to greatly affect the psychological state of patients, making them feel uneasy or conversely, cheering them up. By clarifying the characteristics of facial expression recognition ability in patients with Lewy body disease, the aim of this study is to examine points to facilitate smooth communication between caregivers and patients with the disease whose cognitive function has deteriorated. Methods During the period from March 2016 to July 2017, we examined the characteristics of recognition of the six facial expressions of “happiness,” “sadness,” “fear,” “anger,” “surprise,” and “disgust” for 107 people aged 60 years or more, both outpatient and inpatient, who hospital specialists had diagnosed with Lewy body diseases of Parkinson’s disease, Parkinson’s disease with dementia, and dementia with Lewy bodies. Based on facial expression recognition test results, we classified them by cluster analysis and clarified features of each type. Results In patients with Lewy body disease, happiness was kept unaffected by aging, age of onset, duration of the disease, cognitive function, and apathy; however, recognizing the facial expression of fear was difficult. In addition, due to aging, cognitive decline, and apathy, the facial expression recognition ability for sadness and anger decreased. In particular, cognitive decline reduced recognition of all of the facial expressions except for happiness. The test accuracy rates were classified into three types using the cluster analysis: “stable type,” “mixed type,” and “reduced type”. In the “reduced type”, the overall facial recognition ability declined except happiness, and in the mixed type, recognition ability of anger particularly declined. Conclusion There were several facial expressions that the Lewy body disease patients were unable to accurately identify. Caregivers are recommended to make an effort to compensate for such situations with language or body contact, etc., as a way to convey correct feeling to the patients of each type.

Kojima et al. Environmental Health and Preventive Medicine
Characteristics of facial expression recognition ability in patients with Lewy body disease
Yuriko Kojima 0
Tomohiro Kumagai 0
Tomoo Hidaka 0
Takeyasu Kakamu 0
Shota Endo 0
Yayoi Mori 0
Tadashi Tsukamoto 2
Takashi Sakamoto 2
Miho Murata 2
Takehito Hayakawa 1
Tetsuhito Fukushima 0
0 Department of Hygiene and Preventive Medicine, Fukushima Medical University School of Medicine , Hikarigaoka 1, Fukushima 960-1295 , Japan
1 Research Center for Social Studies of Health and Community, Ritsumeikan University , Tojiinkita-machi 56-1, Kita-ku, Kyoto 603-8577 , Japan
2 Department of Neurology, National Center of Neurology and Psychiatry , Kogawahigashi-cho 4-1-1, Kodaira, Tokyo 187-8551 , Japan
Background: The facial expression of medical staff has been known to greatly affect the psychological state of patients, making them feel uneasy or conversely, cheering them up. By clarifying the characteristics of facial expression recognition ability in patients with Lewy body disease, the aim of this study is to examine points to facilitate smooth communication between caregivers and patients with the disease whose cognitive function has deteriorated. Methods: During the period from March 2016 to July 2017, we examined the characteristics of recognition of the six facial expressions of “happiness,” “sadness,” “fear,” “anger,” “surprise,” and “disgust” for 107 people aged 60 years or more, both outpatient and inpatient, who hospital specialists had diagnosed with Lewy body diseases of Parkinson's disease, Parkinson's disease with dementia, and dementia with Lewy bodies. Based on facial expression recognition test results, we classified them by cluster analysis and clarified features of each type. Results: In patients with Lewy body disease, happiness was kept unaffected by aging, age of onset, duration of the disease, cognitive function, and apathy; however, recognizing the facial expression of fear was difficult. In addition, due to aging, cognitive decline, and apathy, the facial expression recognition ability for sadness and anger decreased. In particular, cognitive decline reduced recognition of all of the facial expressions except for happiness. The test accuracy rates were classified into three types using the cluster analysis: “stable type,” “mixed type,” and “reduced type”. In the “reduced type”, the overall facial recognition ability declined except happiness, and in the mixed type, recognition ability of anger particularly declined. Conclusion: There were several facial expressions that the Lewy body disease patients were unable to accurately identify. Caregivers are recommended to make an effort to compensate for such situations with language or body contact, etc., as a way to convey correct feeling to the patients of each type.
Facial expression recognition; Basic facial expressions; Aging; Parkinson's disease; Lewy body disease; Dementia
Background
The six facial expressions of “happiness,” “sadness,” “fear,”
“anger,” “surprise,” and “disgust” are agreed to be basic
expressions regardless of race, language, and culture [
1, 2
].
In previous studies, facial expression recognition tests have
been conducted with a method presenting stimuli based on
the classification of these six basic expressions. As a result,
it turned out that there are diseases that hinder recognition
of facial expressions. According to Ruffman et al.’s
meta-analysis of previous research comparing elderly and
young people’s facial expression recognition [3], the average
accuracy rate on the facial expression recognition test for
young people compared with the elderly group was
happiness (98%) > sadness (89%) > surprise (87%) > disgust
(81%) > fear (79%), so even without the effect of aging,
there was a difference for young people in the degree of
difficulty of recognition for each facial expression.
In psychiatry and cognitive neurology, it has been
reported that autistic children, people with schizophrenia,
alexithymic individuals, and traumatic brain injury patients
have poor facial expression recognition ability [
4–7
].
Parkinson’s disease (PD) patients showed a decline in
recognition ability of fear and disgust; patients with myotonic
dystrophy type I had decreased recognition of anger and
disgust; and those with Huntington’s disease showed a
decline in recognition ability of disgust [
8–11
].
There has also been research with respect to facial
expression recognition in the elderly. Calder et al. found that
although there was a decline in recognition ability of fear
and anger, there was no decline in recognition ability of
disgust [
12
]. The results of McDowell et al. indicate that
there was a decline in recognition ability of neutral and
negative facial expressions, but there was no decline in
recognition ability of happiness [
13
]. Phillips et al. found a
decline in recognition ability of anger and sadness [
14
].
Although the results of these previous studies are not
completely consistent, they do show that there is not a
decline in recognition ability of all facial expressions due to
the influence of aging in elderly people; rather, recognition
of fear, anger, and sadness is reduced, while the ability to
recognize happiness does not decrease.
As an extension of the elderly study, Maki et al. used
results of perceptual matching challenges of patients with
Alzheimer’s disease to compare with results of healthy
elderly people and young adults and found no significant
difference with the healthy elderly [
15
]. Results of this
study suggest that happiness, which is a positive facial
expression, does not show a decline due to age, but any
consistent trends about facial expression recognition
ability of elderly people with dementia are not clear.
After the onset of PD, the number of those with dementia
increases with the passage of years; after 20 years, it has
been reported that 83% of patients will have dementia [
16
].
Various types of PD-related dementia include Parkinson’s
disease with dementia (PDD) [
17
], in which dementia
develops several years after the onset of PD, as distinguished
from dementia with Lewy bodies (DLB) [
18
], in which
dementia develops within 1 year after the appearance of
Parkinsonism. PD, PDD, and DLB have come to be collectively
referred to as Lewy body disease [
19
] because proteins
called alpha-synuclein accumulate and form aggregates
called Lewy bodies which can be seen in nerve cells.
This study focused on Lewy body disease and revealed
the characteristics of facial recognition function in Lewy
body disease patients which has not been clarified, with
classification made using cluster analysis. Based on the
results of this analysis, we examined points to be
considered for facilitating smooth communication between
caregivers and patients with impaired cognitive function.
Methods
Subjects
This study was conducted from March 2016 to July 2017
by specialists from the National Center of Neurology and
Psychiatry Hospital, Japan, with 107 subjects (outpatient
and inpatient) 60 years of age or older diagnosed with
Lewy body disease (PD [
20
], PDD [
17
], and DLB [
21
]).
Subjects were judged by a specialist to be able to
communicate intentionally, and the breakdown by diagnosis was
PD (80 people), PDD (8 people), and DLB (19 people).
Measures
Survey items included basic attributes, a cognitive
function test, face-to-face questionnaires (depression scale,
anxiety scale, and motivation reduction scale), and a test
for facial expression recognition by facial stimuli.
Electronic medical record data was used for the basic
attributes of age, sex, onset age, and duration of disease.
Tests for basic attributes
For the cognitive function test, the Mini-Mental State
Examination (MMSE) was used [
22
]. A score of 24 points or more
was determined as non-dementia, and a score of 23 points
or less was defined as dementia; for the depression scale,
subjects completed the Geriatric Depression Scale
short-version (GDS-15), a simple 15-question test with two
choices, “yes” or “no,” which has shown relatively high
sensitivity [
23
] as an evaluation criterion for depressive symptoms
of PD [
24
]. A score of 6 or more suggests depression. The
State-Trait Anxiety Inventory (STAI) was used as an anxiety
scale [
25
], making it possible to measure both state anxiety
and trait anxiety with 20 questions each. Fifty-five points or
more points to high anxiety; the Apathy Scale was used to
measure reduction in motivation [
26
], and a score of 16
points or more has been determined to suggest apathy.
Test for facial expression recognition
Regarding the test for facial expression recognition based
on facial stimulation (the facial expression recognition
test), this study used 42 facial pictures classified by Ekman
et al. [
27
] as the six basic expressions (happiness, sadness,
fear, anger, surprise, and disgust) reported to be
commonly recognized in all countries [
1, 2
], in order to
investigate how subjects understand others’ feelings. Subjects
were randomly presented with facial pictures one by one
showing one of the six facial expressions and instructed to
decide which of the six basic facial expressions that
picture was expressing. No particular time limit was set, and
the photograph was placed so as to be in the field of view
of the subject the whole time.
Statistical analysis
The mean and standard deviation were found for the
basic attributes of the subject: age, onset age, and
duration of disease; MMSE score; GDS-15 score; anxiety
score, state anxiety (STAI-1) and trait anxiety (STAI-2);
and Apathy Scale score. Median and 25–75 percentiles
were calculated for the accuracy of recognition test.
Subjects were classified into three groups based on the
diagnosis (PD, PDD, and DLB). Then, the accuracy rates
of the facial expression recognition test were calculated by
the classification. The Mann-Whitney U test was used for
comparisons of the facial expression recognition accuracy
rate, and the degree of relevance between the basic
attribute items of the subject and the facial expression
recognition accuracy rate was evaluated by Spearman rank
correlation. Subsequently, hierarchical cluster analysis
(Ward method) was performed to identify the
characteristics of the subject from the combination patterns of the
six facial expression recognition test accuracy rates.
To describe the characteristics of each cluster, we
compared the age, onset age, sex, MMSE score, Apathy Scale
score, and diagnosis of the patients. We categorized the
cutoff values of MMSE and Apathy Scale scores as 24 and 16,
respectively. For age and onset age, we used one-way analysis
of variance (ANOVA) test and the Bonferroni method for
multiple comparisons. Chi-square test and residual analysis
were used for sex, MMSE score, Apathy Scale score, and
diagnosis. The cells were considered to have significantly
more subjects than expected when the adjusted standardized
residual values were greater than 1.96, whereas the cells were
considered to have significantly fewer subjects than expected
when the values were lower than − 1.96.
All statistical analyses were performed by using
statistical software SPSS Statistics version 24 (IBM Corp.,
Armonk, NY, USA). The significance level was set at 5%.
Ethics
The objectives and content of this research, management
of personal information, and anonymity of answers were
all explained in writing, and written consent was received.
This study was approved by the Fukushima Medical
University Ethics Committee (approval number 2426) and
the ethics committee of the National Center of Neurology
and Psychiatry Hospital (approval number A2015-82).
Results
A comparison of facial expression recognition test accuracy
rates is shown in Table 1. There was no significant
difference between PD + PDD and DLB in their facial expression
recognition test accuracy rate. It was determined that there
were no vision-related effects, visual hallucinations of DLB.
Mean, median, and interquartile range of basic
attribute items of subjects are shown in Table 2. The overall
average age was 74.7 years of age (minimum 60 years,
maximum 94 years), and the average age of males was
73.5 years while the average age of females was 75.9 years
old. The overall average age of onset was 67.9 years of
age (minimum 48 years, maximum 88 years) with an
average age of onset for males at 66.7 years and for
females 69.0 years. The overall average duration of the
disease was 6.8 years (minimum less than 1 year, maximum
19 years), with an average duration of disease in males
as 6.9 years and females 6.8 years.
The mean and median values of MMSE, GDS-15,
STAI, and Apathy Scale were within the range of normal
levels for total, male, female, PD, and DLB categories.
The variation seen in the interquartile range was also
roughly constant for the total, male, and female values.
Table 3 shows a comparison of facial expression
recognition test accuracy by gender. With the facial expression
of happiness, the results were significantly higher for
women than for men. Outside of happiness, a statistically
significant difference could not be seen with sadness, fear,
anger, surprise, and disgust. A ranking of the facial
expression recognition test accuracy rates showed the same
trend, and in both men and women, the rankings were
happiness > sadness and surprise > anger > disgust > fear.
The relevance between subjects’ basic attribute items
and facial expression recognition test accuracy rates was
evaluated by Spearman’s rank correlation with results
shown in Table 4. Of the six facial expressions, except for
happiness and fear, there were significant positive
correlations between the facial expressions of sadness and
surprise, sadness and disgust, anger and surprise, and
surprise and disgust. There were significant negative
correlations between age and the three facial expressions of
sadness, anger, and surprise. There were significant
negative correlations between the age of onset and anger and
surprise. Other than happiness, MMSE had significant
positive correlations with facial expression recognition of
sadness, fear, anger, surprise, and disgust. There were
significant negative correlations between Apathy Scale score
and the two facial expressions of sadness and anger.
From the combination patterns of the six facial
expression recognition test accuracy rates, hierarchical cluster
analysis was conducted, and the facial expression
recognition test accuracy rates (median) were classified into three
types (Fig. 1). The cluster with a facial expression
recognition test accuracy rate higher than the other two clusters
was labeled the “stable type” (45 subjects). The ranking of
each facial expression recognition test accuracy rate of the
stable type was happiness (100%) > sadness (87.5%) and
surprise (87.5%) > anger (71.4%) > disgust (49.6%) > fear
(16.7%).
The cluster with an overall accuracy rate lower than
the other two clusters was labeled the “reduced type” (22
subjects). The ranking of each facial expression
recognition test accuracy rate of the reduced type was happiness
(92.9%) > surprise (62.5%) > anger (42.9%) > sadness
(37.5%) > disgust (16.7%) and fear (16.7%). The reduced
type was characterized by inability to identify sadness
and disgust in the facial expression recognition test.
The cluster with accuracy rates between the stable
type and the reduced type was labeled the “mixed type”
(40 subjects). The ranking of each facial expression
recognition test accuracy rate of the mixed type was
happiness (100%) > sadness (75.0%) and surprise (75.0%) >
disgust (33.3%) > anger (28.6%) > fear (16.7%).
Happiness and fear had the same accuracy rates when
comparing the facial expression recognition test
accuracy rates of the mixed type and stable type, and the
mixed type was lower in sadness, surprise, disgust, and
anger. In particular, a major feature of the mixed type
was that the accuracy rate of anger was less than that of
the reduced type.
Discussion
This study divided the facial expression recognition ability
into three types: stable type, mixed type, and reduced type,
and revealed their characteristics. Reduced type was
characterized by poor performance in the facial expression
recognition test regarding sadness and disgust faces, and it
is assumed that this result was caused by the decline of
cognitive function, since there were a statistically large
number of subjects with MMSE scores of less than 24 in
this group. The mixed type group had a lower accuracy
rate of regarding identifying angry expressions than the
other two groups. Mixed type was a specific group with
poor performance of recognition test only for anger face
in spite of their better function of cognition than reduced
type. It may be difficult for mixed type patients to
understand the emotion of anger even when their caregivers
show angry expressions. Thus, particular care is required
when communicating the emotion of anger when treating
patients who fall under this category.
With regard to happiness, the only positive expression
in the six basic expressions, the facial expression
recognition test accuracy remained consistently high in this
research for all types (stable type, mixed type, and
reduced type), revealing that facial expression recognition
of happiness does not change due to age or cognitive
deterioration. This supports the results of McDowell et al.
[
13
] and Maki et al. [
15
]. It has also been reported that
happiness (smiling) has a higher predominance of
perception and identification than other facial expressions, such as
disgust and sadness [
28, 29
]. Although the facial expression
recognition test accuracy rate of happiness was high for
males, results showed females judged even more accurately
than men. There are sex differences in facial expression
recognition, which is consistent with the finding that female
facial expression recognition ability was higher than that of
men [
30–32
]. It could be said that this reflects that
generally, compared to men, women are more likely to
express emotions and are more sensitive to the feelings of
others.
The expression of surprise is neither positive nor
negative; rather, it can be regarded as a neutral expression.
Age, age of onset, and cognitive function correlated, and
facial expression recognition performance showed a
gradual decline due to aging and cognitive decline,
which is consistent with the findings obtained from
previous work by McDowell et al. [
13
].
*Significant one-way ANOVA for continuous variables or chi-square test for discrete variables
a, bMultiple comparison by Bonferroni method
†Adjusted standardized residual <-1.96
‡Adjusted standardized residual > 1.96
SD standard deviation
In relation to the negative expressions of disgust and
fear, this study included many stable type subjects without
cognitive decline who scored less than a 50% accuracy rate
for disgust and fear, findings which are consistent with a
previous study by Kan et al. [
8
], in which PD patients
without dementia had difficulty recognizing the facial
expressions of disgust and fear. Additionally, fear was not
influenced by aging, age of onset, or the duration of the
disease, and the results of the facial expression recognition
test were consistently low at 16.7% for the stable type,
mixed type, and reduced type. With regard to disgust,
although it was not affected by aging, age of onset, and the
duration of the disease, there was a difference between the
three types. Since compared to PD and PDD, DLB is a
disease characterized by having frequent occurrences of
visual hallucinations, auditory hallucinations, delirium, etc.
[
33
], facial expression recognition tests targeting DLB
patients had not been proactively conducted thus far. In the
current study, we considered the possibility that DLB
patients would not be able to correctly judge the facial
photographs of people or to be able to participate in facial
expression recognition tests due to the visual
hallucinations. However, it was determined that there was no effect
of visual hallucinations, suggesting that facial expression
recognition tests can be performed with DLB patients
henceforth.
A major characteristic of anger, a negative expression,
was that its facial expression recognition test accuracy
rate was significantly lower in the mixed type than the
reduced type. Previous studies reported that an angry
facial expression can be correctly identified more often
and quicker than other expressions, since this face is a
signal of direct threat [
34, 35
]. It has been reported that
antisocial people with low empathy score lower in facial
expression recognition tests that consist of negative
facial expressions such as anger and fear [
36, 37
].
Furthermore, there is genetic modulation for facial recognition
which neutral face tends to be recognized as anger [
38
].
Looking by diagnosis in the cluster analysis results, it
can be seen that the mixed type included as many as 10
DLB subjects, which is half of the total of 19 patients
with DLB. The remarkable decrease in the accuracy rate
of anger seen in the mixed type may be from the
possibility of a characteristic of DLB.
The current study had some limits. First, it was a
cross-sectional study, and the cause and effect relationship
could not be clarified. In addition, the representativeness
of the sample was insufficient because the subjects of this
study were recruited from single medical institution and
also were small-sized. The populations of future studies
should be larger than that of the current study.
Conclusions
The patterns of facial expression recognition ability in
patients with Lewy body disease were classified into three
types: stable type, mixed type, and reduced type, and each
category was defined. The reduced type comprised of
subjects with an overall low accuracy rate for all facial
expressions except happiness. The accuracy rate of anger in the
mixed type was particularly low. We recommend that
caregivers make an effort to compensate for such unrecognized
feelings with language, body contact, etc., as a way to
convey their intended feelings to the patients.
Abbreviations
DLB: Dementia with Lewy bodies; GDS-15: Geriatric Depression Scale
Short-version; MMSE: Mini-Mental State Examination; PD: Parkinson’s disease;
PDD: Parkinson’s disease with dementia
Availability of data and materials
Through the contract with NCNP, we cannot provide data, but if permission
from NCNP (Dr. Murata) is obtained, it may be possible.
Authors’ contributions
YK was the research practitioner. TF was the research supervisor. TKu created
the research protocols and provided medical advice and statistical analysis
guidance. TKa provided statistical analysis guidance and advice. THi provided
psychological evaluation advice. YM provided data organization and advice.
THa and SE provided statistics and analysis guidance and advice. MM
provided medical advice and selection of subjects and supervised the
implementation of research at NCNP. TT provided the medical advice and
selection of subjects. TS provided anonymization work and its management.
All authors read the final manuscript and gave approval.
Ethics approval and consent to participate
The objectives and content of this research, management of personal
information, and anonymity of answers were all explained in writing, and
written consent was received. This study was approved by the Fukushima
Medical University Ethics Committee (approval number 2426) and the ethics
committee of the National Center of Neurology and Psychiatry Hospital
(approval number A2015-82).
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
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